Semantics-based Framework for Personalized Access to TV Content: the iFanzy Use Case

The ICT landscape is developing into a highly-interactive distributed environment in which people interact with multiple devices (e.g. portable devices such as mobile phones and home equipment such as TV’s) and multiple applications (e.g. computer programs such as Web browsers and dedicated Web services) [1]. Globally, the industry is being driven by the shift away from old models from physical space to digital space. New methods emerge for getting content such as TV programs via the Web. Almost half of the people want to watch TV content on their PC’s; they want to make a bridge between a TV and a PC, perhaps even sitting in a home office [2]. The information overload is enormous and the content presented is hardly adapted to the prior knowledge, to the preferences and to the current situation of the user. Personalization in information retrieval and information presentation has therefore become a key issue and a key ingredient of the so-called “Web 2.0” applications. However, such personalization is still local and cannot be used in the context of other information services: e.g. personalized information is only valid within one Web application such as an online TV Guide1. Moreover, the online TV Guide cannot cater for different “modes” of a user, e.g. when watching a program himself, or when watching together with friends [3]. Thus, main aspects we cover in this work are Data integration of distributed collections, a Context modeling framework for temporal and spatial-specific viewpoints, User modeling in a contextualized form, and Personalized presentation of the combined information about data, context and user. In this paper we present SenSee, a semantics-based framework for providing personalized access to TV content in a cross-media environment. It allows for an integrated view on data harvested from heterogeneous and distributed Web sources. The ultimate goal is to support individual and group TV viewers